Latour and Woolgar’s ‘cycle of scientific credibility’ as a basis for conceptualizing business school strategy

Review of Managerial Science - Drawing on contemporary and historical discourse around UK business schools and insights from the sociology of scientific knowledge, we argue that business schools...     

Indigenous research methodology – weaving a research interface

ABSTRACT

Indigenous research Knowledges and methodologies have existed over millennia, however it is only recently that Indigenous scholars have been able to challenge institutional Western hegemony to reclaim sovereignty in the research space. Despite the high volume of quantitative research describing Aboriginal and Torres Strait Islander health, there has been limited evaluation of the value added through incorporation of Indigenous Knowledges and methodologies. ‘Research at the interface’ has been discussed as an Indigenous research methodology for researchers to contextualise and inform their research practices, between Indigenous and Western systems of knowledge. In this article we address the significance of ‘research at the interface’ for Aboriginal and Torres Strait Islander research, as an exciting opportunity for innovation to ensure strength, self-determination and resilience for Aboriginal and Torres Strait Islander communities engaged in research. We also introduce weaving a methodology for ‘research at the interface’ as a process for conceptualising Indigenous and quantitative research methodologies at the interface.     

Social-ecological research in urban natural areas: an emergent process for integration

Urban Ecosystems - Understanding the structure and function of urban landscapes requires integrating social and ecological research. Here, we integrate parallel social and ecological assessments of...     

Not just a number? NEETs,data and datalogical systems

This paper draws on empirical research with NEET populations (16–24-year-olds not in education, employment or training) in the U.K. in order to engage with issues around identification, data and metrics produced through datalogical systems. Our aim is to bridge contemporary discourses around data, digital bureaucracy and datalogical systems with empirical material drawn from a long-term ethnographic project with NEET groups in Leeds, U.K. in order to highlight the way datalogical systems ideologically and politically shape people’s lives. We argue that NEET is a long-standing data category that does work and has resonance within wider datalogical systems. Secondly, that these systems are decision-making and far from benign. They have real impact on people’s lives – not just in a straightforwardly, but in obscure, complex and uneven ways which makes the potential for disruption or intervention increasingly problematic. Finally, these datalogical systems also implicate and are generated by us, even as we seek to critique them.     

Bayesian analysis of multivariate survival data using Monte Carlo methods

This paper deals with the analysis of multivariate survival data from a Bayesian perspective using Markov-chain Monte Carlo methods. The Metropolis along with the Gibbs algorithm is used to calculate some of the marginal posterior distributions. A multivariate survival model is proposed, since survival times within the same group are correlated as a consequence of a frailty random block effect. The conditional proportional-hazards model of Clayton and Cuzick is used with a martingale structured prior process (Arjas and Gasbarra) for the discretized baseline hazard. Besides the calculation of the marginal posterior distributions of the parameters of interest, this paper presents some Bayesian EDA diagnostic techniques to detect model adequacy. The methodology is exemplified with kidney infection data where the times to infections within the same patients are expected to be correlated.     

Principles for Conduct of Pest Risk Analyses: Report of an Expert Workshop

The North American Free Trade Agreement (NAFTA) and the General Agreement on Tariffs and Trade (GATT) have focused attention on risk assessment of potential insect, weed, and animal pests and diseases of livestock. These risks have traditionally been addressed through quarantine protocols ranging from limits on the geographical areas from which a product may originate, postharvest disinfestation procedures like fumigation, and inspections at points of export and import, to outright bans. To ensure that plant and animal protection measures are not used as nontariff trade barriers, GATT and NAFTA require pest risk analysis (PRA) to support quarantine decisions. The increased emphasis on PRA has spurred multiple efforts at the national and international level to design frameworks for the conduct of these analyses. As approaches to pest risk analysis proliferate, and the importance of the analyses grows, concerns have arisen about the scientific and technical conduct of pest risk analysis. In January of 1997, the Harvard Center for Risk Analysis (HCRA) held an invitation-only workshop in Washington, D.C. to bring experts in risk analysis and pest characterization together to develop general principles for pest risk analysis. Workshop participants examined current frameworks for PRA, discussed strengths and weaknesses of the approaches, and formulated principles, based on years of experience with risk analysis in other setting and knowledge of the issues specific to analysis of pests. The principles developed highlight the both the similarities of pest risk analysis to other forms of risk analysis, and its unique attributes.